The relationship between cognitive insight and cognitive performance among individuals with at-risk mental state for developing psychosis
Introduction
For decades, numerous researchers have explored the factors contributing to the onset of psychosis. For example, insight into ones' own illness, that is, “clinical insight,” has been believed to be one of the main factors that influences the differences between individuals with fully psychotic illness and those with subthreshold symptoms (Lappin et al., 2007). In this line, the “cognitive model” is suggested to be a promising model for explaining the cognitive mechanisms relating to the onset of psychosis and maintenance of positive symptoms (Garety et al., 2001) and has been supported by accumulating neurobiological findings (Garety et al., 2007). This model underscores the role of biased processes of reasoning and appraisal of anomalous experiences or thoughts. In the same vein, Beck et al. (2004) proposed the concept of “cognitive insight.” This was defined as the ability in individuals with psychosis to re-evaluate their own anomalous experiences and correct distorted beliefs and misinterpretations regarded as associated with the development and maintenance of psychotic symptoms. Given the proposal that the critical determinant of psychosis may be appraisal of anomalous experiences (Garety et al., 2001, Lappin et al., 2007, Morrison and Baker, 2000), cognitive insight should also be one of the critical factors that influences differentiation between psychosis and non-psychosis. To measure an individual's capacity for cognitive insight, Beck et al. (2004) developed the Beck Cognitive Insight Scale (BCIS).
The BCIS is a 15-item self-report questionnaire that comprises two principle components—“self-reflectiveness,” which includes 9 items assessing the ability to re-evaluate unusual experiences and correct erroneous judgments, and “self-certainty,” which comprises 6 items representing one's tendency to be overconfident about one's own judgment. Previous studies have corroborated the reliability and validity of the BCIS (e.g., Pedrelli et al., 2004, Uchida et al., 2009) and showed that individuals with psychotic disorders exhibit lower cognitive insight (Engh et al., 2007, Martin et al., 2010, Warman et al., 2007). Furthermore, cognitive insight has been found to be associated with positive and negative symptoms (Bora et al., 2007, Pedrelli et al., 2004, Tranulis et al., 2008); neurocognitive dysfunctions (Nair et al., 2014, for a review); and variations in brain structure, including hippocampal volume (Buchy et al., 2010) and volume of the frontal, parietal, and temporal cortices (Buchy et al., 2016).
Although cognitive insight has been hypothesized to influence the onset of psychosis and maintenance of positive symptoms, its nature in individuals with a high risk for developing psychosis remains unclear. So far, only two studies have investigated this topic. One study (Uchida et al., 2014) found impairments in cognitive insight—namely, excessively high self-certainty—and a relationship between high self-certainty and attenuated delusional symptoms in individuals with the at-risk mental state (ARMS; Yung et al., 2004). In the other study, however, individuals with ARMS showed intermediate self-certainty scores between healthy controls (HCs) and individuals with schizophrenia, who showed significantly higher self-certainty scores than did HCs (Kimhy et al., 2014). Furthermore, Individuals with ARMS with markedly severe unusual thought content showed significant associations between high self-certainty and high suspiciousness. Thus, excessively high self-certainty might underlie the severity of attenuated psychotic symptoms in ARMS.
Recently, the relationship between cognitive insight and cognitive functions has drawn the interest of some researchers. One recent meta-analysis of seven studies in patients with psychotic disorders revealed that a composite index of cognitive insight was positively associated with total cognition, memory, and executive function (Nair et al., 2014). On the other hand, different relationship between sub-components of cognitive insight, that is, self-certainty and self-reflectiveness, and cognitive functions were also observed; higher self-certainty was significantly related to poorer performance on total cognition, IQ, and memory; however, there was no significant correlation between self-reflectiveness and performance in any neurocognitive domain. However, as was noted by the authors of the study, there were several limitations in this meta-analysis; the pooled sample of this meta-analysis was demographically and clinically heterogeneous; categorization of cognitive tests was somewhat crude; relatively recent and limited literature might increase publication bias. In fact, significant correlation between self-certainty and executive function (Cooke et al., 2010, Gilleen et al., 2011, Orfei et al., 2010) and those between self-reflectiveness and working memory (Orfei et al., 2010) and verbal memory (Buchy et al., 2010) were observed in individual studies, even though the meta-analysis failed to find such associations. Therefore, the relationship between cognitive insight and cognitive function does not appear to have been conclusively determined and further study is necessary.
To date, however, there has been no study on the relationship between cognitive insight and neurocognitive function among individuals with ARMS, that showed neurocognitive dysfunctions similar to full psychosis, including verbal memory, visual memory, processing speed, general intelligence, and executive function (Fusar-Poli et al., 2012, Bora et al., 2014). Thus, in the current study, we investigated the correlations between cognitive insight and cognitive performance in individuals with ARMS and compared them with correlations in healthy controls. We hypothesized that similar to full psychosis, cognitive functions in subjects with ARMS correlate with their poorer cognitive insight, particularly with self-certainty.
Section snippets
Participants
Fifty subjects with ARMS and 29 HCs who were Japanese speakers and aged between 14 and 35 participated in this project. The participants with ARMS were users of the SAFE Clinic, an expert clinical setting for individuals with ARMS (Mizuno et al., 2009, Katsura et al., 2014). The data shown in this article are baseline data collected from individuals with ARMS who provided their informed consent on participation in this project. The Comprehensive Assessment of At-Risk Mental States-Japanese
Demographic data
Table 1 summarizes the demographic data. The difference in age between the two samples was marginally significant, and the gender ratio did not show significant difference between two groups. The years of education and estimated IQ of the HC group were higher than those of the ARMS group.
Clinical characteristics
Table 2 contains the fulfilled ultra-high risk criteria, clinical variables, and information on medication in the ARMS group. All but 3 participants with ARMS fulfilled the criteria of attenuated psychotic
Discussion
To our knowledge, this is the first study to examine the association of cognitive insight and neurocognitive function among individuals with ARMS. The results showed that higher self-certainty in the ARMS group was significantly correlated with worse performance in terms of the numbers of CAs and PENs in the WCST; it was not, however, associated with any other domain of neurocognitive function. The poorer performance on the WCST indicates that participants had difficulty in shifting to the
Role of funding source
This work was supported by JSPS KAKENHI Grant Numbers 22390219, 23791307, 25860984, and 16K10240.
Contributors
NO and KM designed the study and wrote the manuscript. HM and KM contributed to managing the project. NO, KM, CO, TK, FI, and KM recruited and clinically evaluated the participants. YH administered cognitive assessment. NO, MK, and CO managed the data. NO analyzed the data and MK, CO, TK, YH, AS, KI, FI and KM assisted NO with analysis and interpretation of the data. They also approved the final manuscript.
Conflicts of interest
All authors declare no conflicts of interest for the work presented here.
Acknowledgement
We thank Emi Sunakawa, Shiori Sato, Mayumi Saito, Aya Takahashi, Tomohiro Uchida, and Rie Koshimichi for their help with the management and preparation of the data.
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